Written by:
Executive Director, Computational Pathology, Oncology R&D, AstraZeneca
Vice President, Image Data Sciences, Computational Pathology, Oncology R&D, AstraZeneca
Associate Director, AI Research, AstraZeneca
Immuno-oncology has opened a new frontier to treat cancer. However, not all cancer patients are benefitting from immunotherapies.
Tumour biopsies shed light on the various types of cancer puzzle by providing a deep, detailed spotlight on the immune system’s reaction to cancer cells. But this only gives us a partial picture, as biopsies can only profile a small part of a tumour at a time.
To better map the immunological landscape of cancer within the body, we are harnessing an emerging technique called immunoPET. Powered by our growing computational pathology expertise, immunoPET could guide physicians’ decisions on the optimal treatments for a patient and support future immunotherapy research.
Boosting response rates to transformative immuno-oncology
Immunotherapies such as checkpoint inhibitors have revolutionised the approach to treating solid tumours. These treatments, which include drug classes such as immune checkpoint inhibitors and cytokines, enable the immune system to destroy cancer cells more easily and can provide durable benefits to many patients.
While immunotherapies have been transformative for some patients, there is still work to be done to realise their full potential. For example, typically fewer than half of patients given checkpoint inhibitors respond to the therapy1. One common reason for this is that tumours can respond differently than healthy cells to a given immunotherapy, even within the same patient.
Understanding more about the bigger picture of cancer and the immune system within the body could therefore help to guide therapeutic options and improve outcomes with smarter cancer treatment combinations.
Biopsies offer limited insights into tumours
How can we predict which tumours will respond well to immunotherapy? One clue to the puzzle is a group of immune cells called cytotoxic T lymphocytes, also known as CD8-positive (CD8+) cells.
CD8+ cells are central to the immune system’s anti-cancer surveillance and response. If they infiltrate a tumour and attack it, then the tumour is more likely to respond to immunotherapy. On the flip side, tumours that are ignored by CD8+ cells are typically resistant to immunotherapy.
One of the most common ways to tell if a tumour will respond to immunotherapy in oncology is by conventional pathology - taking a biopsy, staining a thin tissue section to reveal the immune cells, and analysing the tissue section under the microscope. This technique, coupled with rapid advances in data science and computational diagnostics, provides rich and detailed information about what immune cells are present, and whether they are attacking the cancer cells.
However, one tumour biopsy only lets us glimpse a small part of the tumour – this may not be enough to provide the full immunological picture of cancer throughout the body. In patients with metastatic disease, for instance, some tumour sites may be vulnerable to immunotherapy, while others may not. Even within a single tumour growth, some regions of abnormal cells may be more resistant to invasion by CD8+ cells than others.
Relying only on tumour biopsies, with their deep but narrow focus on a small region of disease, could partly explain the variability we see in responses to immunotherapy.
Revealing the immune landscape of cancer within the body
An emerging technique for cancerous tumours based on positron emission tomography (PET) scanning, called immunoPET, has the potential to reveal more about the global immune landscape of a cancer patient.
Patients undergoing PET are injected with a radioactive tracer that emits positrons, which are then detected by a scanner. In the most common form of immunoPET, the tracer is linked to a compound that seeks out and binds to CD8+ T cells, revealing their location throughout the body.
Combining immunoPET with another imaging technique such as computerised tomography (CT) scanning or magnetic resonance imaging (MRI), can show which tumours have CD8+ cells present and which do not, in addition to the relative levels of infiltration.
Unlike tissue biopsies, which provide snapshots of tumours within the body, immunoPET maps the immunological landscape of cancer within the whole body. This can provide vital context about how CD8+ cells are behaving at the tumour site as well as other important locations including the spleen and bone marrow. In the case of metastatic cancer, the technique can also signal which secondary tumours might respond to immunotherapy based on whether or not they have CD8+ cells present.
ImmunoPET is also non-invasive, making it easier for patients to undergo more than one session to track changes in CD8+ cells.
A technology with potential to grow
We are currently testing out the potential of immunoPET in a collaboration with the specialist company ImaginAb, which has developed an antibody-based CD8 PET tracer. The technology has been put to the test in early clinical development to visualise CD8+ cell activity in patients dosed with our candidate antibody treatments for cancer.
As immunoPET develops, it could support the development of treatments that can boost the number of CD8+ cells infiltrating tumours.
The technique could also empower physicians to provide effective cancer treatments on multiple fronts. In patients with metastatic cancer, for example, healthcare professionals could use immunoPET to decide to treat one tumour growth with immunotherapy and another with surgery.
While our early results from immunoPET are promising, a lot of development is still required to get it ready for wider use. One challenge is using the large, complex datasets produced by immunoPET to the full. To solve this, we are designing algorithms powered by artificial intelligence (AI) to streamline immunoPET analyses and provide detailed insights about the actions of the immune system within the body.
Another limitation to be overcome is the low resolution of current PET scanners. However, new generations of PET scanners and radioactive tracers are in development, which could unlock the wider use of immunoPET in precision medicine in cancer.
Bioimaging is experiencing remarkable growth
Rapid advances in scanning and computing technology are driving a boom in bioimaging and computational pathology innovation, and we are demonstrating leadership in this exciting space. One example is AI-driven computer vision software that can help radiologists to analyse medical images more quickly.
While no imaging technology will answer every question about the location and underlying biology of cancer within the body, immunoPET holds a lot of promise and we are excited to move forward with our partners to explore its potential and applications. A major goal is to identify the situations where immunoPET will be most informative, and to see if it can be used to stratify patients in clinical trials of immunotherapy.
Although it’s still early days, the technology could pave the way for more effective and targeted cancer therapies and immunotherapies, further expanding the potential of these life-changing treatments.
